Local field correction PIV: on the increase of accuracy of digital PIV systems

Local field correction PIV: on the increase of accuracy of digital PIV systems Cross-correlation Particle Image Velocimetry (PIV) has become a well known and widely used experimental technique. It has been already documented that difficulties arise resolving velocity structures smaller than the interrogation window. This is caused by signal averaging over this window. A new cross-correlation PIV method that eliminates this restriction is presented. The new method brings some other enhancements, such as the ability to deal with large velocity gradients, seeding density inhomogeneities, and high dispersion in the brightness of the particles. The final result is a method with a remarkable capability for accurately resolving small scale structures in the flow, down to a few times the mean distance between particles. When compared to particle tracking velocimetry, the new method is capable of obtaining measurements at high seeding density concentrations. Therefore, better overall performance is obtained, especially with the limited resolutions of video CCDs. In this paper, the new method is described and its performance is evaluated and compared to traditional PIV systems using synthetic images. Application to real PIV data are included and the results discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

Local field correction PIV: on the increase of accuracy of digital PIV systems

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Publisher
Springer-Verlag
Copyright
Copyright © 1999 by Springer-Verlag Berlin Heidelberg
Subject
Engineering; Engineering Fluid Dynamics; Fluid- and Aerodynamics; Engineering Thermodynamics, Heat and Mass Transfer
ISSN
0723-4864
eISSN
1432-1114
D.O.I.
10.1007/s003480050335
Publisher site
See Article on Publisher Site

Abstract

Cross-correlation Particle Image Velocimetry (PIV) has become a well known and widely used experimental technique. It has been already documented that difficulties arise resolving velocity structures smaller than the interrogation window. This is caused by signal averaging over this window. A new cross-correlation PIV method that eliminates this restriction is presented. The new method brings some other enhancements, such as the ability to deal with large velocity gradients, seeding density inhomogeneities, and high dispersion in the brightness of the particles. The final result is a method with a remarkable capability for accurately resolving small scale structures in the flow, down to a few times the mean distance between particles. When compared to particle tracking velocimetry, the new method is capable of obtaining measurements at high seeding density concentrations. Therefore, better overall performance is obtained, especially with the limited resolutions of video CCDs. In this paper, the new method is described and its performance is evaluated and compared to traditional PIV systems using synthetic images. Application to real PIV data are included and the results discussed.

Journal

Experiments in FluidsSpringer Journals

Published: Jul 2, 1999

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